Publications of Peter Benner

Przybilla, J.; Pontes Duff, I.; Goyal, P. K.; Benner, P.: Balanced Truncation of Descriptor Systems with a Quadratic Output. (2024)

Baran, B.; Benner, P.; Saak, J.; Stillfjord, T.: Numerical Methods for Closed-Loop Systems with Non-Autonomous Data. (2024)

Mlinarić, P.; Benner, P.; Gugercin, S.: Interpolatory Necessary Optimality Conditions for Reduced-order Modeling of Parametric Linear Time-invariant Systems. (2024)

Naumann, C.; Kumar, T. S.; Vettermann, J.; Geist, A.; Saak, J.; Benner, P.; Ihlenfeldt, S.: Training of Artificial Neural Networks with Reduced-Order Models for the Prediction of Thermal Errors on Machine Tools. Research Square (2024)

Zuyev, A.; Benner, P.: Iterative Approximations of Periodic Trajectories for Nonlinear Systems with Discontinuous Inputs. (2023)

Goyal, P. K.; Pontes Duff, I.; Benner, P.: Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference. (2023)

Yildiz, S.; Goyal, P. K.; Benner, P.: Linearly Implicit Global Energy Preserving Reduced-order Models for Cubic Hamiltonian Systems. (2023)

Zhang, J.; Heiland, J.; Benner, P.; Du, X.: Frequency-dependent Switching Control for Disturbance Attenuation of Linear Systems. (2023)

Sun, S.; Feng, L.; Chan, H. S.; Miličić, T.; Vidaković-Koch, T.; Benner, P.: Parametric Dynamic Mode Decomposition for Nonlinear Parametric Dynamical Systems. (2023)

Kour, K.; Dolgov, S.; Benner, P.; Stoll, M.; Pfeffer, M.: A Weighted Subspace Exponential Kernel for Support Tensor Machines. (2023)

Goyal, P. K.; Pontes Duff, I.; Benner, P.: Inference of Continuous Linear Systems from Data with Guaranteed Stability. (2023)

Baran, B.; Benner, P.; Saak, J.: Riccati-feedback Control of a Two-dimensional Two-phase Stefan Problem. (2022)

Goyal, P. K.; Benner, P.: Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning. (2021)

Sarna, N.; Benner, P.: Learning Reduced Order Models from Data for Hyperbolic PDEs. (2021)

Goyal, P. K.; Benner, P.: LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes. (2021)

Goyal, P. K.; Benner, P.: Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint. The Symbiosis of Deep Learning and Differential Equations Workshop at NeurIPS 2021, 9 pages (2021)

Goyal, P. K.; Daas, H. A.; Benner, P.: Low-Rank and Total Variation Regularization and Its Application to Image Recovery. (2020)

Banagaaya, N.; Ali, G.; Grundel, S.; Benner, P.: Automatic Decoupling and Index-aware Model-Order Reduction for Nonlinear Differential-Algebraic Equations. (2020)

Yue, Y.; Feng, L.; Benner, P.: An Adaptive Pole-Matching Method for Interpolating Reduced-Order Models. (2019)

Benner, P.; Onwunta, A.; Stoll, M.: On the Existence and Uniqueness of the Solution of a Parabolic Optimal Control Problem with Uncertain Inputs. (2018)